decision theory判決論英文版
上傳時間： 2016-10-31
上傳用戶：亞亞娟娟123
NeC4.5 is a variant of C4.5 decision tree, which could generate decision trees more accurate than standard C4.5 decision trees, through regarding a neural network ensemble as a pre-process of C4.5 decision tree.
標簽： decision 4.5 accurate generate
上傳時間： 2013-12-10
上傳用戶：anng
模式識別中多類分類問題決策樹間接Induction of decision Trees
標簽： Induction decision Trees of
上傳時間： 2013-12-09
上傳用戶：cooran
Many of the pattern fi nding algorithms such as decision tree, classifi cation rules and clustering techniques that are frequently used in data mining have been developed in machine learning research community. Frequent pattern and association rule mining is one of the few excep- tions to this tradition. The introduction of this technique boosted data mining research and its impact is tremendous. The algorithm is quite simple and easy to implement. Experimenting with Apriori-like algorithm is the fi rst thing that data miners try to do.
標簽： 64257 algorithms decision pattern
上傳時間： 2014-01-12
上傳用戶：wangdean1101
This demo shows the BER performance of linear, decision feedback (DFE), and maximum likelihood sequence estimation (MLSE) equalizers when operating in a static channel with a deep null. The MLSE equalizer is invoked first with perfect channel knowledge, then with an imperfect, although straightforward, channel estimation algorithm. The BER results are determined through Monte Carlo simulation. The demo shows how to use these equalizers seamlessly across multiple blocks of data, where equalizer state must be maintained between data blocks.
標簽： performance likelihood decision feedback
上傳時間： 2013-11-25
上傳用戶：1079836864
％For the following 2-class problem determine the decision boundaries ％obtained by LMS and perceptron learning laws.
標簽： boundaries the following determine
上傳時間： 2016-11-26
上傳用戶：guanliya
c4.5 關于決策樹decision tree的matlab實現程序
上傳時間： 2017-01-02
上傳用戶：lanhuaying
this is an weka tool source code implemented in java used for decision tree
標簽： implemented decision source this
上傳時間： 2014-07-12
上傳用戶：181992417
The first decision, that has to be made for the AVR platform, is to select the development environment you want to use, either ImageCraft s ICCAVR or GNU s AVR-GCC. The commercial ImageCraft Compiler offers an advanced IDE and is the first choice of most professional developers using a Windows PC. The GNU compiler is available for Linux and Windows.
標簽： development the decision environm
上傳時間： 2017-04-21
上傳用戶：從此走出陰霾
this is decision tree ID3 algorithm, this algorithm is one of decision tree algorithm like cart, chaid, c4.5, etc
標簽： algorithm decision this tree
上傳時間： 2017-04-23
上傳用戶：498732662
